It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity (≥2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. We studied data from UK Biobank (428,199 participants; aged 37–73; recruited 2006–2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96–1.30)), whereas those with ≥2 LTCs had 48% higher risk; RR 1.48 (1.28–1.71). Compared with no cardiometabolic LTCs, having 1 and ≥2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12–1.46) and 1.77 (1.46–2.15), respectively. Polypharmacy was associated with a dose response higher risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI ≥40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09–3.78); 2.79 (2.00–3.90); 2.66 (1.88–3.76); 2.13 (1.46–3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19.

UK Biobank is a prospective cohort study of around half-a-million general population participants, recruited between 2006 and 2010, with baseline studies at recruitment and multiple assessments since. From 2014 to date, magnetic resonance imaging (MRI) has been pursued in a participant sub-sample, with the aim to scan around n = 100k. This sub-sample is studied widely and therefore understanding its relative characteristics is important for future reports. We aimed to quantify psychological and physical health in the UK Biobank imaging sub-sample, compared with the rest of the cohort. We used t-tests and χ² for continuous/categorical variables, respectively, to estimate average differences on a range of cognitive, mental and physical health phenotypes. We contrasted baseline values of participants who attended imaging (versus had not), and compared their values at the imaging visit versus baseline values of participants who were not scanned. We also tested the hypothesis that the associations of established risk factors with worse cognition would be underestimated in the (hypothesized) healthier imaging group compared with the full cohort. We tested these interactions using linear regression models. On a range of cognitive, mental health, cardiometabolic, inflammatory and neurological phenotypes, we found that 47 920 participants who were scanned by January 2021 showed consistent statistically significant ‘healthy’ bias compared with the ∼450 000 who were not scanned. These effect sizes were small to moderate based on Cohen’s d/Cramer’s V metrics (range = 0.02 to −0.21 for Townsend, the largest effect size). We found evidence of interaction, where stratified analysis demonstrated that associations of established cognitive risk factors were smaller in the imaging sub-sample compared with the full cohort. Of the ∼100 000 participants who ultimately will undergo MRI assessment within UK Biobank, the first ∼50 000 showed some ‘healthy’ bias on a range of metrics at baseline. Those differences largely remained at the subsequent (first) imaging visit, and we provide evidence that testing associations in the imaging sub-sample alone could lead to potential underestimation of exposure/outcome estimates.

Aims : To compare the incidence and mortality risk for cardiovascular diseases (CVD) [CVD and also ischaemic heart disease (IHD), myocardial infarction (MI), stroke, and heart failure (HF)] among people with different types of diets—including vegetarians, fish eaters, fish and poultry eaters, and meat-eaters—using data from UK Biobank.Methods and results : A total of 422 791 participants (55.4% women) were included in this prospective analysis. Using data from a food frequency questionnaire, four types of diets were derived. Associations between types of diets and health outcomes were investigated using Cox proportional hazard models. Meat-eaters comprised 94.7% of the cohort and were more likely to be obese than other diet groups. After a median follow-up of 8.5 years, fish eaters, compared with meat-eaters, had lower risks of incident CVD {hazard ratios (HR): 0.93 [95% confidence intervals (CI): 0.88–0.97]}, IHD [HR: 0.79 (95% CI: 0.70–0.88)], MI [HR: 0.70 (95% CI: 0.56–0.88)], stroke [HR: 0.79 (95% CI: 0.63–0.98)] and HF [HR: 0.78 (95% CI: 0.63–0.97)], after adjusting for confounders. Vegetarians had lower risk of CVD incidence [HR: 0.91 (95% CI: 0.86–0.96)] relative to meat-eaters. In contrast, the risk of adverse outcomes was not different in fish and poultry eaters compared with meat-eaters. No associations were identified between types of diets and CVD mortality.Conclusion : Eating fish rather than meat or poultry was associated with a lower risk of a range of adverse cardiovascular outcomes. Vegetarianism was only associated with a lower risk of CVD incidence.

Discretionary screen time (time spent viewing a television or computer screen during leisure time) is an important contributor to total sedentary behaviour, which is associated with increased risk of mortality and cardiovascular disease (CVD). The aim of this study was to determine whether the associations of screen time with cardiovascular disease and all-cause mortality were modified by levels of cardiorespiratory fitness, grip strength or physical activity. In total, 390,089 participants (54% women) from the UK Biobank were included in this study. All-cause mortality, CVD and cancer incidence and mortality were the main outcomes. Discretionary television (TV) viewing, personal computer (PC) screen time and overall screen time (TV + PC time) were the exposure variables. Grip strength, fitness and physical activity were treated as potential effect modifiers. Altogether, 7420 participants died, and there were 22,210 CVD events, over a median of 5.0 years follow-up (interquartile range 4.3 to 5.7; after exclusion of the first 2 years from baseline in the landmark analysis). All discretionary screen-time exposures were significantly associated with all health outcomes. The associations of overall discretionary screen time with all-cause mortality and incidence of CVD and cancer were strongest amongst participants in the lowest tertile for grip strength (all-cause mortality hazard ratio per 2-h increase in screen time (1.31 [95% confidence interval: 1.22–1.43], p < 0.0001; CVD 1.21 [1.13–1.30], p = 0.0001; cancer incidence 1.14 [1.10–1.19], p < 0.0001) and weakest amongst those in the highest grip-strength tertile (all-cause mortality 1.04 [0.95–1.14], p = 0.198; CVD 1.05 [0.99–1.11], p = 0.070; cancer 0.98 [0.93–1.05], p = 0.771). Similar trends were found for fitness (lowest fitness tertile: all-cause mortality 1.23 [1.13–1.34], p = 0.002 and CVD 1.10 [1.02–1.22], p = 0.010; highest fitness tertile: all-cause mortality 1.12 [0.96–1.28], p = 0.848 and CVD 1.01 [0.96–1.07], p = 0.570). Similar findings were found for physical activity for all-cause mortality and cancer incidence. The associations between discretionary screen time and adverse health outcomes were strongest in those with low grip strength, fitness and physical activity and markedly attenuated in those with the highest levels of grip strength, fitness and physical activity. Thus, if these associations are causal, the greatest benefits from health promotion interventions to reduce discretionary screen time may be seen in those with low levels of strength, fitness and physical activity.

Background: higher grip strength is associated with better health outcomes. The optimal way to report grip strength (i.e. absolute vs. relative) for prediction, however, remains to be established.Methods: in participants (aged 37–73 at baseline) from the UK Biobank, we examined the associations of grip strength, expressed in absolute terms (kilograms) and relative to anthropometric variables, with mortality and disease incidence, after exclusion of the first 2 years of follow-up, and compared risk predictions scores of handgrip strength when differentially expressed.Results: of the 356 721 participants included in the analysis 6,234 died (1.7%) and 4,523 developed CVD (1.3%) over a mean follow-up of 5.0 years (ranging from 3.3 to 7.8) for mortality and 4.1 years (ranging from 2.4 to 7.0) for disease incidence data. As expected, baseline higher grip strength was associated with lower risk of all-cause and cause specific mortality and incidence. These associations did not meaningfully differ when grip-strength was expressed in absolute terms, vs. relative to height, weight, fat-free mass, BMI, fat-free mass index and fat-free mass, or as z-scores. Similarly the different ways of expressing grip strength had little effect on the ability of grip strength to improve risk prediction, based on C-index change, of an office-based risk score.Conclusions: the ability of grip strength to predict mortality is not altered by changing how it is expressed.

Background: Recent efforts to address the obesity epidemic have focused on sugar consumption, especially sugar-sweetened beverages. However, sugar takes many forms, is only one contributor to overall energy consumption and is correlated with other health-related lifestyle factors. The objective was to investigate the associations with all-cause mortality of sugar- and artificially sweetened beverages and naturally sweet juices. Methods: Setting: UK Biobank, UK. Participants joined the UK Biobank study from 2006 to 2010 and were followed up until 2016; 198,285 men and women aged 40–69 years were eligible for this study (40% of the UK Biobank), of whom 3166 (1.6%) died over a mean of 7 years follow-up. Design: prospective population-based cohort study. Exposure variables: dietary consumption of sugar-sweetened beverages, artificially sweetened beverages, naturally sweet juices (100% fruit/vegetable juices) and total sugar intake, self-reported via 24-h dietary assessment tool completed between 2009 and 2012. Main outcome: all-cause mortality. Cox regression analyses were used to study the association between the daily intake of the above beverages and all-cause mortality. Models were adjusted for sociodemographic, economic, lifestyle and dietary confounders. Results: Total energy intake, total sugar intake and percentage of energy derived from sugar were comparable among participants who consumed > 2/day sugar-sweetened beverages and > 2/day fruit/vegetable juices (10,221 kJ/day versus 10,381 kJ/day; 183 g versus 190 g; 30.6% versus 31.0%). All-cause mortality was associated with total sugar intake (highest quintile adj. HR 1.28, 95% CI 1.06–1.55) and intake of sugar-sweetened beverages (> 2/day adj. HR 1.84, 95% CI 1.42–2.37) and remained so in sensitivity analyses. An association between artificially sweetened beverage intake and mortality did not persist after excluding deaths in the first 2 years of follow-up (landmark analysis) nor after excluding participants with recent weight loss. Furthermore, the inverse association between fruit/vegetable juice intake and mortality did not persist after additional adjustment for a diet quality score. Conclusions: Higher mortality is associated with sugar-sweetened beverages specifically. The lack of an adverse association with fruit/vegetable juices suggests that source of sugar may be important and the association with artificially sweetened beverage may reflect reverse causation.